There is a growing concern that a radiological dispersal device (“dirty bomb”) could be used by terrorist particularly in places with a high density of people or in areas of high value commercial or government properties and facilities. Since such a device would be small enough to be man or vehicle portable, the best probability to detect and interdict such a device is to widely distribute a network of spectroscopic radiation sensors that are mobile, man portable, work without operator intervention and are connected to central command and control sensor and optionally to one another. This provides the most general and dynamic scheme to monitor and map a large, uncontrolled area potentially full of people. An additional important benefit of such a system is that it can detect radioactive sources that, although not intended as terrorist threats, still pose public safety problems. For example, there have been incidents where untended industrial and medical sources have been released without proper safeguards into public areas.
Any local measurement of radiation has contributions from Naturally Occurring Radioactive Materials (NORM) in that locale and possible non-NORM sources ranging from medical isotopes (from patients for example which just underwent a stress test), industrial isotopes not properly secured or being used for nefarious purposes and Special Nuclear Materials (SNM) that can be used in a nuclear device (or a nuclear device already assembled). Detection algorithms must estimate the contributions of both NORM backgrounds and the presence of possible non-NORM radioactive sources.
The detection of natural and manmade sources using distributed radiation sensors over large geographic areas poses unique and complex networking and computational problems. It has been demonstrated that fusing spectral data from sensors that are in proximity offers higher sensitivity and low false alarm rates, for example, as described in PCT/US2014/012330, published as WO 2014/0133687, and U.S. patent application Ser. No. 14/237,088, all of which are hereby incorporated herein by reference in their entirety. The spatial scale over which spectral data fusion is useful is determined by intrinsic sensor properties such as the absolute efficiency, and energy resolution of the sensor. External properties of importance are the energy, and strength of the radioactive source and any shielding materials that are between the source and sensor. For example, spatial scales of order few times 10 m are obtained for handheld spectroscopic radiation sensors. Thus in a large system of tens of thousands of sensors in a city there may be a large number of clusters of sensors in which real time sharing (of order seconds) of spectral data through a server or system of servers is helpful to reap the full benefits of spectral data fusion. Efficient and responsive network systems can generate a dynamic set of clusters that allow full data sharing for optimal detection performance. For sensor nodes that are isolated (i.e., nodes that do not benefit from real time data sharing), data transmission will consist of node position, health, background spectra measurements and any detection alarms. The network SmartServer can dynamically determine if open bandwidth is present so that even isolated nodes can dynamically transmit spectral data for background mapping. Optionally, if the Server determines that open bandwidth is not present the node can locally log data and upload to the system when bandwidth is available and/or there is a local “base” connection to the server. It is also desirable for two way communication between command and control provided through the SmartServer. Usually the required bandwidth for such communication consists of passing alarms, texts, etc. and is typically small as compared to that required for data fusion.
As discussed above, a high spatial resolution statistically significant map of the NORM background is crucial for high sensitivity searches for non-NORM radiation sources. NORM background can vary significantly over small spatial scales particularly in urban environmental with a large variety of construction materials are present. Therefore, fine scale measurements of the background are highly desirable to ensure high sensitivity to the presence of non-NORM sources of radiation while retaining a low rate of false alarms. A distributed network of radiation sensors with spectroscopic capabilities is an effective method for obtaining large area coverage of NORM background. Particularly if the sensors are mobile, they can differentiate isotopes of interest and can do this without operator intervention or supervision. Therefore, optimal network architecture must be able to collect, store and distribute this constantly updated background map. In a large system, a SmartServer can improve performance by allocating the available resources between the search for non-NORM sources of radiation and the collection and distribution of background data.